User’s Guide¶

Setting up the Dataset¶

Download the IOSTAR dataset, take note of it’s root directory and configure the data access using the bob command-line configuration utility. For example:

$ conda activate your-bob-env
(your-bob-env) $ bob config set bob.db.iostar.datadir /path/to/root/of/iostar
(your-bob-env) $ bob config show #to check

You can than check if your local version of the dataset is compatible with this interface and has the standard directory tree:

$ conda activate your-bob-env
(your-bob-env) $ bob_dbmanage.py iostar checkfiles
checkfiles completed sucessfully

Protocols¶

This packages provides two default protocols:

default_vessel for binary vessel segmentation
default_od for binary optic disc segmentation

Each protocol uses the train/test split as proposed by Meyer et al. (2017):

@InProceedings{10.1007/978-3-319-59876-5_56,
    author="Meyer, Maria Ines
    and Costa, Pedro
    and Galdran, Adrian
    and Mendon{\c{c}}a, Ana Maria
    and Campilho, Aur{\'e}lio",
    editor="Karray, Fakhri
    and Campilho, Aur{\'e}lio
    and Cheriet, Farida",
    title="A Deep Neural Network for Vessel Segmentation of Scanning Laser Ophthalmoscopy Images",
    booktitle="Image Analysis and Recognition",
    year="2017",
    publisher="Springer International Publishing",
    address="Cham",
    pages="507--515",
    isbn="978-3-319-59876-5"
}

The first 20 images are used for training and the remaining 10 for testing.